I am using DESeq2 to analysis rna-seq data with 8 biological replicates, which are paired samples. These samples are of primary cells, where variation between samples is expected. As this is a paired analysis, I am not removing batch effects.

When I plot PCA, I could do not see that the samples are separated in to two groups.

This just means that the subject effect is larger than the treatment effect. But you can still perform inference on the treatment effects using the ~subject + treat design. If you want, you can look at the results for significant genes using plotCounts, to see how treatment effects within subjects look.